Big data has already taken the shipping industry by storm. Commercial shippers and other end users are increasingly in demand for cutting-edge solutions like marine data analysis. Big data is utilized in the shipping sector to perform predictive analysis and regulate sensors on ships to reduce delays and increase productivity. Big data analytics-enhanced decision making is actively being applied to prevent and foresee additional expenditures, and it can be used throughout the duration of a ship's life. Despite the fact that we now have access to large amounts of quantifiable data on navigation, machinery and equipment performance, meteorology, and other factors, we are only beginning to explore the application of predictive analysis using big data in the maritime industry. This study aims at bringing together and comparing various predictive models using machine learning algorithms that can be used for different maritime applications.